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Safety, Volume 9, Issue 2
June 2023 - 23 articles
Cover Story: Motorways are typically the safest road environment in terms of injury crashes per vehicle kilometres; however, given the high severity of crashes occurring therein, there is still space for improvements. This study aims to compare the classification performance of five machine learning techniques for predictions of crash risk levels of motorway segments. The response variable of the models was the crash risk level of the considered motorway segments, while the predictors were various road design characteristics and naturalistic driving behaviour metrics. Among the five techniques, the Random Forest model achieved the best classification performance, suggesting that it could be used as a highly promising proactive road safety tool for identifying potentially hazardous motorway segments. View this paper
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Safety - ISSN 2313-576X